基于图像天空区域分割的去雾算法

doi:10.12305/j.issn.1001-506X.2023.06.03

Abstract

Abstract:

In order to improve the haze removal effect of images, an image haze removal algorithm based on transmissivity synthesis of sky region segmentation is proposed in this paper. The rough segmentation threshold is determined based on the probability distribution function constructed by haze image with the combination of iterative threshold segmentation with dark and bright channels and the maximum connectivity. Guided filtering is used to enhance the difference of the pixel gray between sky and non-sky regions to achieve the accurate segmentation. Logarithmic adaptive transformation is adopted to estimate the transmissivity in sky region, and the improved dark channel prior algorithm is used to estimate the transmissivity in non-sky region. The image was defogged by synthesizing the transmissivity of the corresponding pixels. Experimental results show that compared with other defogging algorithms, the algorithm presented in this paper achieves improvements in all objective indexes, which accurately segments sky and non-sky regions, and achieves good overall visual effect of defogging images.

Key words: sky segmentation, image defogging, dark channel prior, transmittance mapping

CLC Number:

TP391.41

Jingrong SUN, Zhezhe CHEN, Linchang XIE, Mengxin DU, Shibin SONG. Haze removal algorithm based on image sky region segmentation[J]. Systems Engineering and Electronics, 2023, 45(6): 1606-1615.

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参数	去雾算法
参数	He算法	Meng算法	Berman算法	潘健鸿算法	Mei算法	本文算法
平均耗时	12.240 1	7.762 4	5.634 1	6.214 6	3.906 4	4.164 5

Haze removal algorithm based on image sky region segmentation

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